The Urban Challenge is over – six of the eleven finalists completed the course. Stanford, Tartan Racing and Victor Tango all finished within a few minutes of each other, just before DARPA’s 6-hour time limit. Ben Franklin, MIT and Cornell also finished, but it looks like they were outside the time limit. The DARPA judges have now got to collate all the data about how well the robots obeyed the rules of the road, and will announce a winner tomorrow morning. It’s going to be very close. From watching the webcast, it looks like either Stanford or Tartan Racing will take the top spot, but making the call between them will be very hard. Both put in almost flawless performances.

Six hours of urban driving, without any human intervention, is quite a remarkable feat. In fact, watching the best cars, I quickly forgot that they weren’t being driven by humans. That’s really quite amazing. I can’t think of any higher praise for the achievement of the competitors.

There were some thrills and spills along the way – TerraMax rammed a building, TeamUCF wandered into a garden, and MIT and Cornell had a minor collision. Once the weaker bots were eliminated though, everything went remarkably smoothly. The last four or five hours passed almost without event. MIT clearly had some trouble, randomly stopping and going very slowly on the off-road sections (looks like their sensor thresholds were set too low), but they’re a first time entry, so getting to the finish line at all is a major achievement.

DARPA put on a extremely professional event. In an interview after the finish, DARPA director Tony Tether said he didn’t expect to run another Challenge. It will be interesting to see where autonomous driving goes from here. The top teams have clearly made huge progress, but the technology is still a long way from the point where you’d let it drive the kids to school. Many things about the challenge were simplified – there were no pedestrians to avoid, and the vehicles all had precise pre-constructed digital maps of the race area, specifying things like where the stop lines were. Putting this technology to use in the real world is still some distance away, but much closer than anyone would have imagined five years ago.